Detection of false message in social media

ABSTRACT

Communications in social networking environment are monitored and patterns of sharing a communication are identified. The patterns of sharing are compared to one or more criteria. A first probability of false information in the communication is determined. Responsive to determining the first probability of false information in the communication exceeding a first threshold, an additional validation of the communication is performed. A second probability that the communication contains false information is determined based on the additional validation. Responsive to determining that the second probability indicative of the communication containing false information exceeds a second threshold, an action to reduce dissemination of the communication may be performed.

FIELD

The present application relates generally to computers, and computerapplications, online communications, and more particularly to detectingfalse messages in social media and/or social networking.

BACKGROUND

Online social networking is used widely for online communications amongpeople. In social networking environment, practically anyone can postmessages or content, and it is not easy to tell whether those messagesor content are authentic and credible. For example, some contentpresented in social networking environment may be false, which canconfuse the users and misguide them.

BRIEF SUMMARY

A method of reducing dissemination of false information in a socialnetworking environment, in one aspect, may comprise monitoringcommunications in social networking environment. The method may alsocomprise identifying patterns of sharing a communication of themonitored communications. The method may further comprise comparing thepatterns of sharing to one or more criteria. The method may alsocomprise determining a first probability of false information in thecommunication. The method may further comprise, responsive todetermining the first probability of false information in thecommunication exceeding a first threshold, performing an additionalvalidation of the communication. The method may also comprisedetermining a second probability that the communication contains falseinformation based on the additional validation. The method may furthercomprise, responsive to determining that the second probabilityindicative of the communication containing false information exceeds asecond threshold, performing an action to reduce dissemination of thecommunication.

A system for reducing dissemination of false information in socialnetworking environment, in one aspect, may comprise a memory and ahardware processor connected to the memory. The hardware processor maybe operable to monitor communications in a social networkingenvironment, the communications, the communications received from one ormore user devices and stored in the memory. The hardware processor maybe further operable to identify patterns of sharing a communication ofthe monitored communications. The hardware processor may be furtheroperable to compare the patterns of sharing to one or more criteria. Thehardware processor may be further operable to determine a firstprobability of false information in the communication. Responsive todetermining the first probability of false information in thecommunication exceeding a first threshold, the hardware processor may befurther operable to perform an additional validation of thecommunication. The hardware processor may be further operable todetermine a second probability that the communication contains falseinformation based on the additional validation. Responsive todetermining that the second probability indicative of the communicationcontaining false information exceeds a second threshold, the hardwareprocessor may be further operable to perform an action to reducedissemination of the communication.

A computer readable storage medium storing a program of instructionsexecutable by a machine to perform one or more methods described hereinalso may be provided.

Further features as well as the structure and operation of variousembodiments are described in detail below with reference to theaccompanying drawings. In the drawings, like reference numbers indicateidentical or functionally similar elements.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a flow diagram illustrating a method of the present disclosurein one embodiment.

FIG. 2 is a system diagram illustrating components of the presentdisclosure in one embodiment.

FIG. 3 is a sample message posting on a user interface of a socialnetworking environment.

FIG. 4 illustrates a schematic of an example computer or processingsystem that may implement a false message detection system in oneembodiment of the present disclosure.

DETAILED DESCRIPTION

A method and system may be provided that detect a false message ormessages in a social network communication, and block the message(s)automatically, for example, at an early stage of the communication.Blocking such false messages at an early stage prevents a wide spreadsharing of possible false messages on social networking environment. Theterm messages is used in the present disclosure to broadly refer tocontent, e.g., that can be posted via social networking environment. Thecontent may include text, images, voice, and other media that may beposted or communicated, e.g., in the social networking environment.

Examples of social networking environment include document managementfacility, a social networking site, a shared repository, a file hostingservice allowing file sharing, electronic mail (email), a voice responsesystem, a forum, wiki, an activity stream, and others.

For example, social networking sites allow users to create an onlineprofile for themselves, make connections and/or relationships online,and socialize with others, for example, using social media tools such asblogs, video, images, messaging, etc., to converse and share contentonline, for example, via computer or communication networks.

A forum refers to a discussion area on web sites, e.g., for conversingon line. Users can post messages or comments on messages on a particularforum, e.g., a web site. Messages are posted asynchronously, e.g.,independent of time and place.

A wiki refers to a set of web pages that is edited collaboratively. Awiki application (web application) allows users to add, modify or deletecontent in collaboration with others.

An activity stream is a list of activities performed by an individual ona web site or a social web application.

In one aspect, a method of the present disclosure detects a possiblefalse message posted or presented on social networking environment,e.g., an online social network site or another, based on a predefinedpattern of sharing of the message. The method, in another aspect,predicts a degree of authenticity of the message. Yet in another aspect,the method may block the message for sharing and may send thenotification about the false information, if it is determined that themessage is inappropriate and/or false.

To detect a possible false message, a method of the present disclosurein one embodiment may identify the messages that are shared amongdifferent people and/or different geographical regions. Based on apredefined rule, the method may perform further analysis on the content.For example, the predefined rule can be the total number of sharing,liking, commenting, or another functionality of a social network, forexample, occurring within a period of time, in a particular geographicalregion, and/or particular community. Briefly, “like” or “liking” refersto a functionality that allows users to express their approval ofcontent, for example, recommend content or show agreement with thecontent. In the present disclosure, the term sharing is used to broadlyrefer to sharing, liking, commenting, and/or another functionality thatallow users to see and use the content.

Based on a threshold number of count, e.g., of the sharing, liking,commenting or another, the method may consider the message for furthervalidation. The method may extract information, metadata, semanticcontent about the message and associated comments. The method mayperform further investigation such as an Internet search from theidentified information of the message. The method may consider thesearch results and validate the posted message against the searchresults. If the method finds that the message is inappropriate and has apoor degree of authenticity, the method may automatically block themessage for sharing. The method may also request the original submitterto provide a reference of the message. The method may also notify otherusers about the above information.

FIG. 1 is a flow diagram illustrating a method of the present disclosurein one embodiment. The method for example reduces dissemination of falseinformation in social networking environment. Social networkingenvironment may include one or more of document management facility, asocial networking site, a shared repository, a file hosting serviceallowing file sharing, email, a voice response system, a forum, wiki, anactivity stream, and others.

At 102, the method may include monitoring communications in a socialnetworking environment. For example, data entered on a user's device viaa user interface of a social networking software, platform or like toolrunning on a hardware processor, which may be stored in memory oranother storage device by the social networking software, platform orlike tool, may be received or retrieved. Such receiving may be performedperiodically or in real time as the data is entered and/or stored.

For example, the social networking application or another applicationmay detect content posted on the site and monitor for a number ofsharing of the content among users. Once any content is posted in socialnetworking site and gains at least a threshold limit of sharing,software or an application installed in social networking site mayperform contextual analysis of the posted content. Contextual analysismay include image object analysis, text extraction from image, keywordextraction from text, video content analysis, etc. The software mayperform semantic analysis to identify the information content, e.g.,search the Internet to find any authentic information sources associatedwith the content. The software may also search location information ofthe content, and may perform a survey in that locality to validate thecontent. The survey can be performed by sending information to thesocial network user of that locality, and asking for feedback.

Examples of communications may include, but are not limited to,postings, documents or files (e.g., in hypertext markup language (html)or other formats), page, picture, video, audio recording, email message,and others.

At 104, the method may include identifying patterns of sharing acommunication in the social networking environment. A pattern of sharingmay include the speed of sharing (e.g., number of sharing in a timeinterval), locality of sharing, comparing the profile of the users whoare sharing, time of sharing, and other attributes with respect to thesharing. Such patterns may be used in predicting a degree of abnormalityin the content of the communication, e.g., that is monitored at 102.

At 106, the method may include comparing the patterns of sharing to oneor more criteria. The criteria may have one or more predefined rulesrelated to the pattern of sharing for determining whether there is afirst probability that the communication contains false information. Asocial network server may create such rules and store them in a server.The rules may specify that the content be shared among certain groups ina locality and a threshold limit for the number of sharing. For example,the first probability may be identified if the communications fallwithin the rules, in this example, content is shared among the specifiedgroup in the specified locality. In this case, if it is determined thatthe number of sharing exceeds the threshold limit associated with thisrule, the content validation may be triggered.

At 108, responsive to determining the first probability of falseinformation in the communication exceeding a first threshold, the methodmay include performing an additional validation of the communication.The first threshold may be a predefined value, and may be configurable,for example, by a system administrator of the social networking tool oranother. The first threshold, for example, may also change dynamically.

Performing additional validation, for example, may include performing anInternet search or another database search regarding the information,and analyzing results of the search for evidence of correctness, scam orspam and hoax. In one embodiment, information from the content of thecommunication and associated comments may be used to perform suchsearch. For example, utilizing a natural language processing (NLP)technique, data content (e.g., keywords and phrases) may be extractedfrom the communication and associated comments, metadata describing thecommunication may be extracted, and semantic content may be extracted.

To perform an Internet search, a search engine may be invoked withkeywords or phrases extracted from the communication as parameters.Similarly, database search may be performed using one or more databasesystem query languages with search parameters.

Other examples of additional validation may include, but are not limitedto, sending the communication to one or more validation services such ashoax validation services for determining whether there is a secondprobability that the communication contains false information, checkingwith the entities or localities mentioned in the communication tovalidate the information and check on the authenticity of theinformation. For example, if the content of the communication containsinformation about a certain institution, a request may be made directlyto that institution to validate the authenticity.

At 110, the additional validation determines a second probability thatthe communication contains false information. For example, the Internetsearch may produce results that may be inconsistent with the contentcontained in the communication, a validation service may return a resultthat the content has certain percentage of likelihood that theinformation is not accurate, an entity or locality may not be able toauthenticate the information about itself contained in thecommunication.

In one aspect, the result returned from the additional validation may becompared to a second threshold. For example, the result may benormalized into a normalized metric value as a second probability andcompared to the second threshold.

At 112, responsive to determining that the second probability indicativeof the communication containing false information exceeds a secondthreshold, the method may include performing an action to reducedissemination the communication (e.g., determined to have falseinformation). The second threshold may be a predefined value, and may beconfigurable, for example, by a system administrator of the socialnetworking tool or another. The second threshold, for example, may alsochange dynamically.

Examples of actions that may be performed to reduce dissemination of theinformation determined to be false may include, but are not limited to,one or more of blocking the entire message or portions thereofdetermined to be false, erasing the entire message or portions thereofdetermined to be false, replacing the entire message or portions thereofdetermined to be false, notifying one or more social networking users,updating or annotating the communication (e.g., posting on the socialnetwork or social media that the communication may be not accurate),providing a option for consumers or users to respond (e.g., by providinga user interface element such as an input area where the users can enterresponses), and requesting additional information such as the origin ofthe message.

FIG. 2 is a system diagram illustrating components of the presentdisclosure in one embodiment. A false information detection module 202may be computer executable module or code, e.g., residing in memory 204of a computer system 206, and/or running on one or more hardwareprocessors 208 such as a central processing unit, field programmablegate array, and/or another hardware processor of a computer system 206.A computer system 206 that the false information detection module 202resides or executes in may also include one or more device interfaces210 for communicating with one or more devices (e.g., a storage device212) and communication or network interface 214 for communicating withother devices via one or more networks 216. The storage device 212 maybe a local storage device (e.g., accessible directly via a deviceinterface 210), or a remote storage device (e.g., accessible via anetwork interface 214).

Social networking environment platform or tool 218 may be a computerexecutable module or code, e.g., residing in memory 220 of a computersystem 222, and/or running on one or more hardware processors 224 suchas a central processing unit, field programmable gate array, and/oranother hardware processor of a computer system 222. A computer system222 that the social networking environment platform or tool 218 residesor executes in may also include a communication or network interface 226for communicating with other devices via one or more networks 216, andone or more device interfaces 228 for communicating with one or moredevices (e.g., a storage device 230). The storage device 230 may be alocal storage device (e.g., accessible directly via a device interface228), or a remote storage device (e.g., accessible via a networkinterface 226).

In one aspect, the false information detection module 202 may run on aseparate computer system from the computer system that is running thesocial networking environment platform or tool 218. In another aspect,the false information detection module 242 may run on the same computersystem that is running the social networking environment platform ortool 218. Yet in another aspect, the false information detection module242 may be an added component of the social networking environmentplatform or tool 218.

The social network environment platform or tool 218 enables one or moreusers to socialize (e.g., communicate) online with one another. Forexample, by registering or creating an account with the social networkenvironment platform or tool 218, the users can post one or moremessages, comment on posted messages, indicate their approval of themessages (e.g., “like” the messages), and/or otherwise share themessages on an online place that that social network environmentplatform or tool 218 provides. For instance, users using user devices232, 234, 236, 238, 240, etc., may perform such tasks, e.g., via a userinterface that is associated with the social network environmentplatform or tool 218. Examples of social networking environment platformor tool 218 include those that implement document management facility, asocial networking site, a shared repository, a file hosting serviceallowing file sharing, email, a voice response system, a forum, wiki, anactivity stream, and others.

The social networking environment platform or tool 218 receives messagesor posting from the user devices (e.g., 232, 234, 236, 238, 240) and maystore them in memory 220 or a storage device 230. The postings appear(e.g., displayed) on a wall (e.g., web page) of a user and any otherusers (e.g., friends, connections) that may have access to theinformation posted by this user. For instance, a user via a userinterface associated with this social networking environment platform ortool 218 that is running on a user device (e.g., 232) may post amessage, e.g., enter text, video, picture, etc, on the user interface.The message is received at the social networking environment platform ortool 218, and saved. The posting may be accessible or displayed forsharing on user devices (e.g., 234, 236, 238, 240) of users who haveconnections (e.g., friends list) with this user (e.g., 232).

The false information detection module (e.g., 202 or 242) may monitorcommunications (e.g., such postings) in a social networking environment.Examples of communications may include, but are not limited to,postings, documents, files, page, picture, hypertext markup language(html), video, audio recording, email message, and others. For example,the false information detection module (e.g., 202 or 242) may monitorcommunications by receiving or retrieving user postings (communications)from memory 220 or storage device 230.

The false information detection module (e.g., 202 or 242) identifiespatterns of sharing a communication in the social networkingenvironment.

The false information detection module (e.g., 202 or 242) compares thepatterns of sharing to one or more criteria. The criteria may have oneor more predefined rules related to patterns of sharing indicative of afirst probability that the communication contains false information.

A social network server may create such rules and store them in aserver, e.g., 212 and/or 214. The rules may specify that the content beshared among certain groups in a certain locality. There may be athreshold limit for the number of sharing associated with this rule. Forexample, the first probability may be identified if the communicationsfall within the rules, in this example, if a communication content isshared among the specified group in the specified locality. In thiscase, if the number of sharing exceeds the threshold limit associatedwith this rule, the content validation may be triggered.

Responsive to determining the first probability of false information inthe communication exceeding a first threshold, the false informationdetection module (e.g., 202 or 242) performs an additional validation ofthe communication. The first threshold may be a predefined value, andmay be configurable, for example, by a system administrator of thesocial networking tool or another. The first threshold, for example, mayalso change dynamically.

To perform additional validation, for example, the false informationdetection module (e.g., 202 or 242) may perform an Internet search oranother database search regarding the information, and analyzing resultsof the search for evidence of correctness, scam or spam and hoax. In oneembodiment, information from the content of the communication andassociated comments may be used to perform such search. For example, thefalse information detection module (e.g., 202 or 242) may utilize anatural language processing (NLP) technique, and extract data content(e.g., keywords and phrases) from the communication and associatedcomments, metadata describing the communication, and semantic content.

The keywords and/or phrases extracted from the communication content maybe used as parameters in performing an Internet search or anothersearch. For example, to perform an Internet search, the falseinformation detection module (e.g., 202 or 242) may invoke a searchengine with keywords or phrases as parameters. Similarly, the falseinformation detection module (e.g., 202 or 242) may perform a databasesearch using one or more database system query languages with searchparameters.

As other examples of additional validation, the false informationdetection module (e.g., 202 or 242) may send the communication to one ormore validation services such as hoax validation services fordetermining whether there is a second probability that the communicationcontains false information, check with the entities or localitiesmentioned in the communication to validate the information and check onthe authenticity of the information. For example, if the content of thecommunication contains information about a certain institution, falseinformation detection module (e.g., 202 or 242) may make a requestdirectly to that institution to validate the authenticity, e.g., bysending an electronic mail or by another communication.

The false information detection module (e.g., 202 or 242), based on theadditional validation, determines a second probability that thecommunication contains false information. For example, the Internetsearch may produce results that may be inconsistent with the contentcontained in the communication, a validation service may return a resultthat the content has certain percentage of likelihood that theinformation is not accurate, an entity or locality may not be able toauthenticate the information about itself contained in thecommunication.

In one aspect, the result returned from the additional validation may becompared to a second threshold. For example, the result may benormalized into a normalized metric value as a second probability andcompared to the second threshold.

Responsive to determining that the second probability indicative of thecommunication containing false information exceeds a second threshold,the false information detection module (e.g., 202 or 242) performs anaction to reduce dissemination the communication (e.g., determined tohave false information). The second threshold may be a predefined value,and may be configurable, for example, by a system administrator of thesocial networking tool or another. The second threshold, for example,may also change dynamically.

Examples of actions that the false information detection module (e.g.,202 or 242) may perform to reduce dissemination of the informationdetermined to be false may include, but are not limited to, one or moreof blocking the entire message or portions thereof determined to befalse, erasing the entire message or portions thereof determined to befalse, replacing the entire message or portions thereof determined to befalse, notifying one or more social networking users, updating orannotating the communication (e.g., posting on the social network orsocial media that the communication may be not accurate), providing aoption for consumers or users to respond (e.g., by providing a userinterface element such as an input area where the users can enterresponses), and requesting additional information such as the origin ofthe message.

The first probability and/or the second probability may represent avalue such as a confidence level that the information is false. Suchvalues (e.g., the first probability, the second probability, theconfidence level) may be displayed or presented with the message to oneor more users (e.g., via a user interface running on devices).

FIG. 3 is a sample message posting on a user interface of a socialnetworking environment, e.g., a social network site. The user interfaceshows a posted message 302 on a user's social networking site web page.The user interface also shows the number of likes for this message andthe number of shares 304.

FIG. 4 illustrates a schematic of an example computer or processingsystem that may implement a false message detection system in oneembodiment of the present disclosure. The computer system is only oneexample of a suitable processing system and is not intended to suggestany limitation as to the scope of use or functionality of embodiments ofthe methodology described herein. The processing system shown may beoperational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with the processing system shown in FIG. 4 may include,but are not limited to, personal computer systems, server computersystems, thin clients, thick clients, handheld or laptop devices,multiprocessor systems, microprocessor-based systems, set top boxes,programmable consumer electronics, network PCs, minicomputer systems,mainframe computer systems, and distributed cloud computing environmentsthat include any of the above systems or devices, and the like.

The computer system may be described in the general context of computersystem executable instructions, such as program modules, being executedby a computer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.The computer system may be practiced in distributed cloud computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed cloudcomputing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

The components of computer system may include, but are not limited to,one or more processors or processing units 12, a system memory 16, and abus 14 that couples various system components including system memory 16to processor 12. The processor 12 may include a module 10 that performsthe methods described herein. The module 10 may be programmed into theintegrated circuits of the processor 12, or loaded from memory 16,storage device 18, or network 24 or combinations thereof.

Bus 14 may represent one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system may include a variety of computer system readable media.Such media may be any available media that is accessible by computersystem, and it may include both volatile and non-volatile media,removable and non-removable media.

System memory 16 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) and/or cachememory or others. Computer system may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 18 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(e.g., a “hard drive”). Although not shown, a magnetic disk drive forreading from and writing to a removable, non-volatile magnetic disk(e.g., a “floppy disk”), and an optical disk drive for reading from orwriting to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media can be provided. In such instances, eachcan be connected to bus 14 by one or more data media interfaces.

Computer system may also communicate with one or more external devices26 such as a keyboard, a pointing device, a display 28, etc.; one ormore devices that enable a user to interact with computer system; and/orany devices (e.g., network card, modem, etc.) that enable computersystem to communicate with one or more other computing devices. Suchcommunication can occur via Input/Output (I/O) interfaces 20.

Still yet, computer system can communicate with one or more networks 24such as a local area network (LAN), a general wide area network (WAN),and/or a public network (e.g., the Internet) via network adapter 22. Asdepicted, network adapter 22 communicates with the other components ofcomputer system via bus 14. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system. Examples include, but are not limitedto: microcode, device drivers, redundant processing units, external diskdrive arrays, RAID systems, tape drives, and data archival storagesystems, etc.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements, if any, in the claims below areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description of the present invention has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The embodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

1.-6. (canceled)
 7. A computer readable storage medium storing a programof instructions executable by a machine to perform a method of reducingdissemination of false information in a social networking environment,the method comprising: monitoring communications in social networkingenvironment; identifying patterns of sharing a communication of themonitored communications, the identifying comprising obtaining a numberof shares associated with content posted in the social networkingenvironment; comparing the patterns of sharing to one or more criteria;determining a first probability of false information in thecommunication; responsive to determining the first probability of falseinformation in the communication exceeding a first threshold, performingan additional validation of the communication; determining a secondprobability that the communication contains false information based onthe additional validation; and responsive to determining that the secondprobability indicative of the communication containing false informationexceeds a second threshold, performing an action to reduce disseminationof the communication.
 8. The computer readable storage medium of claim7, wherein the action comprises one or more of blocking thecommunication from being transmitted, erasing the communication,replacing the communication, notifying one or more users that shared thecommunication, requesting additional information from an originator ofthe communication.
 9. The computer readable storage medium of claim 7,wherein said performing of the additional validation of thecommunication comprises: one or more of performing an Internet search orperforming a database search based on information extracted from thecommunication; and analyzing results of one or more of the Internetsearch or the database search or both.
 10. The computer readable storagemedium of claim 9, wherein the information extracted from thecommunication comprises one or more of keywords parsed from content ofthe communication using a natural language processing technique,metadata associated with the communication, one or more of keywordsparsed from a comment responding to the communication, or metadataassociated with the comment, or combinations thereof.
 11. The computerreadable storage medium of claim 7, wherein the social networkingenvironment comprises a document management facility, a socialnetworking site, a shared repository, a file sharing service, a voiceresponse system, an Internet discussion forum, a wiki, or an activitystream or combinations thereof.
 12. The computer readable storage mediumof claim 7, wherein the communications comprises one or more of anonline posting, a computer file, a web page, a picture, a video, audiorecording, or an email or combinations thereof.
 13. A system forreducing dissemination of false information in social networkingenvironment, comprising: a memory; and a hardware processor connected tothe memory and operable to monitor communications in a social networkingenvironment, the communications received from one or more user devicesand stored in the memory, the hardware processor further operable toidentify patterns of sharing a communication of the monitoredcommunications, the hardware processor operable to obtain a number ofshares associated with content posted in the social networkingenvironment to identify the patterns of sharing, the hardware processorfurther operable to compare the patterns of sharing to one or morecriteria, the hardware processor further operable to determine a firstprobability of false information in the communication, responsive todetermining the first probability of false information in thecommunication exceeding a first threshold, the hardware processorfurther operable to perform an additional validation of thecommunication, the hardware processor further operable to determine asecond probability that the communication contains false informationbased on the additional validation, responsive to determining that thesecond probability indicative of the communication containing falseinformation exceeds a second threshold, the hardware processor furtheroperable to perform an action to reduce dissemination of thecommunication.
 14. The system of claim 13, wherein the action comprisesone or more of blocking the communication from being transmitted,erasing the communication, replacing the communication, notifying one ormore users that shared the communication, requesting additionalinformation from an originator of the communication.
 15. The system ofclaim 13, wherein the hardware processor is operable to perform theadditional validation of the communication by one or more of performingan Internet search or performing a database search based on informationextracted from the communication, and analyzing results of one or moreof the Internet search or the database search or both.
 16. The system ofclaim 15, wherein the information extracted from the communicationcomprises one or more of keywords parsed from content of thecommunication using a natural language processing technique, metadataassociated with the communication, one or more of keywords parsed from acomment responding to the communication, or metadata associated with thecomment, or combinations thereof.
 17. The system of claim 13, whereinthe social networking environment comprises a document managementfacility, a social networking site, a shared repository, a file sharingservice, a voice response system, an Internet discussion forum, a wiki,or an activity stream or combinations thereof.
 18. The system of claim13, wherein the communications comprises one or more of an onlineposting, a computer file, a web page, a picture, a video, audiorecording, or an email or combinations thereof.